Cloud Computing - AWS

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California’s leading transfer college to the University of California and a top provider of affordable career education in Los Angeles—has created a cloud computing certificate, which incorporates content from Amazon Web Services (AWS) and AWS Educate, Amazon’s global initiative to provide students and educators with the resources needed to accelerate cloud-related learning.

Cloud computing—which delivers vast data capacity to organizations of all shapes and sizes without requiring expensive on-site servers—is widely considered the biggest growth arena in technology today. It is also set to open a world of opportunity for Santa Monica College students, in one of the highest paying IT fields.

In just 15 units, SMC’s Cloud Computing Certificate gets students ready to pursue a career in cloud computing and introduces students to AWS technologies. AWS courses cover programming, database management, security, and other essentials

Students from Roosevelt High School in East Los Angeles at Santa Monica College’s Center for Media and Design on Stewart Street. They are part of a cohort taking classes in cloud computing. (Photo Credit: Amy Gaskin)

(left to right) Jose Castro, David Aguilar, Estefania De Luna, and Abel Guillen in a computer lab at SMC’s Center for Media and Design during a cloud computing class. (Photo Credit: Amy Gaskin)

CS 79A: Introduction to Cloud Computing

This course introduces cloud computing which shifts information systems from on-premises computing infrastructure to highly scalable internet architectures. The course provides a solid foundation of cloud computing technologies and provides students with the understanding required to effectively evaluate and assess the business and technical benefits of cloud computing and cloud applications. Students analyze a variety of cloud services (storage, servers and software applications) and cloud providers. Case studies will be used to examine various industry cloud practices and applications. The course also surveys cloud careers and discusses industry demand for cloud skills. ​

CS 79B: Database Essentials in Amazon Web Services

This course addresses cloud database management which supports a number of different approaches for storing data. In the course, students define, operate and scale both SQL and noSQL data storage solutions. This course considers factors that should be balanced during the design of a storage solution. Principles are applied by performing exercises using Amazon RDS and SQL to create and fill tables, retrieve and manipulate data. Object-based APIs are used to serialize objects to Amazon DynamoDB for noSQL solutions. Topics include automated backups, transaction logs, restoration and retention.

Course Objectives

Describe how SQL and noSQL database web services can be used to store data

CS 79C: Computing Engines in Amazon Web Services

In this course, students explore how cloud computing systems are built using a common set of core technologies, algorithms, and design principles centered around distributed systems. Students will use the Amazon Web Services (AWS) Management Console to provision, load-balance and scale their applications using the Elastic Compute Cloud (EC2) and the AWS Elastic Beanstalk. The course discusses, from a developer perspective, the most important reasons for using AWS and examines the underlying design principles of scalable cloud applications.

Course Objectives

Describe the architectural approach used by AWS

Navigate the AWS Management Console

Describe the architectural approach used by AWS' Elastic Beanstalk

Deploy and manage Elastic Beanstalk applications

Scale and Load-Balance cloud application using AWS tools

Deploy EC2 Servers and work with various Amazon Machine Images

CS 79D: Security in Amazon Web Services

This course focuses on protecting the confidentiality, integrity and availability of computing systems and data.Students learn how Amazon Web Service (AWS) uses redundant and layered controls, continuous validation and testing, and a substantial amount of automation to ensure the underlying infrastructure is continuously monitored and protected. Students examine the AWS Shared Responsibility Model and access the AWS Management Console to learn more about security tools and features provided by the AWS platform.

CS 79E: Best Practices in Amazon Web Services

In this advanced course, students will learn how to use the AWS Well-Architected framework that has been developed as a guideline to cloud architects to implement the most secure, high-performing, resilient and efficient infrastructure possible for their applications. Using case studies and class projects, students will apply the five pillars of operational excellence, security, reliability, performance efficiency and cost optimization on AWS architected infrastructures.

Course Objectives

Describe the AWS Well-Architected Framework

Describe design principles and apply the best practices of Operational Excellence in AWS

Describe design principles and apply the best practices of Security in AWS

Describe design principles and apply the best practices of Reliability in AWS

Describe design principles and apply the best practices of Cost Optimization in AWS

Describe design principles and apply the best practices of Performance Efficiency in AWS

CS 79F: Machine Learning on AWS

This course will cover how business decisions can be made into machine learning problems for deeper business insight. We will cover the terms and concepts required to help you learn and build a good foundational understanding of machine learning, artificial intelligence and deep learning. You will learn the various Amazon Web Services Machine Learning stack, Artificial Intelligence and Deep Learning services, using application use cases, frameworks and infrastructure that will allow us to build, train, and deploy learning models at scale. Data is a vital part of machine learning, we will cover how business data is stored, moved and processed throughout the machine learning pipeline.

Course Objectives

List and describe the basics of Machine Learning, Artificial Intelligence and Deep Learning.

Describe the terms and processes to build a machine learning model using the Amazon Web Services platform.

Describe the fundamental concepts of how a business challenge can be modeled in a machine learning model.

Perform mass storage of business data to be used in machine learning model.

Describe how business data can be moved and processed through the machine learning pipeline.